online video course for Graph Algorithms and Problems in Java

About Course

•  

  This is an animated, visual and spatial way to learn data structures and algorithms

  • Our brains process different types of information differently - evolutionarily we are wired to absorb information best when it is visual and spatial i.e. when we can close our eyes and see it
  • More than most other concepts, Data Structures and Algorithms are best learnt visually. These are incredibly easy to learn visually, very hard to understand most other ways
  • This course has been put together by a team with tons of everyday experience in thinking about these concepts and using them at work at Google, Microsoft and Flipkart

  Taught by a Stanford-educated ex-Googler.

  The graph is a data structure that is used to model a very large number of real world problems. It's also an programming interview favorite. The study of graphs and algorithms associated with graphs forms an entire field of study called graph theory.

  • Directed and undirected graphs
  • Adjacency matrices, lists and sets
  • Breadth and Depth-First traversal
  • Topological sort
  • Djikstra's algorithm
  • Bellman-Ford algorithm
  • Prim's algorithm
  • Kruskal's algorithm

Topics covered in this course

• Section 1: Its A Connected World!
  	Lecture 0	You, This Course, and Us!	01:14
  	Lecture 2	Introducing The Graph	15:40
  	Lecture 3	Types Of Graphs	07:21
  	Lecture 4	The Directed And Undirected Graph	14:29
  	Lecture 5	Representing A Graph In Code	08:09
  	Lecture 6	Graph Using An Adjacency Matrix	15:25
  	Lecture 7	Graph Using An Adjacency List And Adjacency Set	17:53
  	Lecture 8	Comparison Of Graph Representations	10:08
  	Lecture 9	Graph Traversal - Depth First And Breadth First	14:56
  Section 2: Graph Algorithms
  	Lecture 10	Topological Sort In A Graph	17:30
  	Lecture 11	Implementation Of Topological Sort	06:56
  Section 3: Shortest Path Algorithms
  	Lecture 12	Introduction To Shortest Path In An Unweighted Graph - The Distance Table	12:38
  	Lecture 13	The Shortest Path Algorithm Visualized	14:15
  	Lecture 14	Implementation Of The Shortest Path In An Unweighted Graph	06:19
  	Lecture 15	Introduction To The Weighted Graph	03:29
  	Lecture 16	Shortest Path In A Weighted Graph - A Greedy Algorithm	18:47
  	Lecture 17	Dijkstra's Algorithm Visualized	14:14
  	Lecture 18	Implementation Of Dijkstra's Algorithm	08:15
  	Lecture 19	Introduction To The Bellman Ford Algorithm	08:40
  	Lecture 20	The Bellman Ford Algorithm Visualized	11:22
  	Lecture 21	Dealing With Negative Cycles In The Bellman Ford Algorithm	07:36
  	Lecture 22	Implementation Of The Bellman Ford Algorithm	06:54
  Section 4: Spanning Tree Algorithms
  	Lecture 23	Prim's Algorithm For a Minimal Spanning Tree	17:27
  	Lecture 24	Use Cases And Implementation Of Prim's Algorithm	09:52
  	Lecture 25	Kruskal's Algorithm For a Minimal Spanning Tree	08:43
  	Lecture 26	Implementation Of Kruskal's Algorithm	07:34
  Section 5: Graph Problems
  	Lecture 27	Design A Course Schedule Considering Pre-reqs For Courses	13:01
  	Lecture 28	Find The Shortest Path In A Weighted Graphs - Fewer Edges Better	14:31

What you will get from this course?

• • Design and implement software using canonical graph algorithms - Djikstra, Prim, Kruskal, Bellman Ford and topological sort
  • Understand the use-cases for the common graph algorithm

Who should buy this course?

• • Please don't enroll for this class if you have already enrolled for our 15-hour course 'From 0 to 1: Data Structures and Algorithms'
  • Computer Science and Engineering grads who are looking to really visualise data structures, and internalise how they work
  • Experienced software engineers who are looking to refresh important fundamental concepts
  • MBA graduates or business professionals who are looking to move to a heavily quantitative role
  • Basic knowledge of programming is assumed, preferably in Java